def test_can_save_and_load_with_landmarks(self):
source_dataset = Dataset.from_iterable([
DatasetItem(id='name0/name0_0001',
subset='test', image=np.ones((2, 5, 3)),
attributes={
'positive_pairs': ['name0/name0_0002'],
'negative_pairs': []
},
annotations=[
Points([0, 4, 3, 3, 2, 2, 1, 0, 3, 0]),
]
),
DatasetItem(id='name0/name0_0002',
subset='test', image=np.ones((2, 5, 3)),
attributes={
'positive_pairs': [],
'negative_pairs': []
},
annotations=[
Points([0, 5, 3, 5, 2, 2, 1, 0, 3, 0]),
]
),
])
with TestDir() as test_dir:
LfwConverter.convert(source_dataset, test_dir, save_images=True)
parsed_dataset = Dataset.import_from(test_dir, 'lfw')
compare_datasets(self, source_dataset, parsed_dataset)
def test_can_save_and_load_with_no_save_images(self):
source_dataset = Dataset.from_iterable([
DatasetItem(
id='name0_0001',
subset='test',
image=np.ones((2, 5, 3)),
annotations=[
Label(0,
attributes={'positive_pairs': ['name0/name0_0002']})
]),
DatasetItem(id='name0_0002',
subset='test',
image=np.ones((2, 5, 3)),
annotations=[
Label(0,
attributes={
'positive_pairs': ['name0/name0_0001'],
'negative_pairs': ['name1/name1_0001']
})
]),
DatasetItem(id='name1_0001',
subset='test',
image=np.ones((2, 5, 3)),
annotations=[Label(1, attributes={})]),
],
categories=['name0', 'name1'])
with TestDir() as test_dir:
LfwConverter.convert(source_dataset, test_dir, save_images=False)
parsed_dataset = Dataset.import_from(test_dir, 'lfw')
compare_datasets(self, source_dataset, parsed_dataset)
def test_can_save_and_load_with_no_format_names(self):
source_dataset = Dataset.from_iterable([
DatasetItem(
id='a/1',
image=np.ones((2, 5, 3)),
annotations=[
Label(0,
attributes={
'positive_pairs': ['name0/b/2'],
'negative_pairs': ['d/4']
})
],
),
DatasetItem(
id='b/2', image=np.ones((2, 5, 3)), annotations=[Label(0)]),
DatasetItem(
id='c/3', image=np.ones((2, 5, 3)), annotations=[Label(1)]),
DatasetItem(
id='d/4',
image=np.ones((2, 5, 3)),
),
],
categories=['name0', 'name1'])
with TestDir() as test_dir:
LfwConverter.convert(source_dataset, test_dir, save_images=True)
parsed_dataset = Dataset.import_from(test_dir, 'lfw')
compare_datasets(self, source_dataset, parsed_dataset)
def test_can_save_and_load_with_meta_file(self):
source_dataset = Dataset.from_iterable([
DatasetItem(
id='name0_0001',
subset='test',
image=np.ones((2, 5, 3)),
annotations=[
Label(0,
attributes={'positive_pairs': ['name0/name0_0002']})
]),
DatasetItem(id='name0_0002',
subset='test',
image=np.ones((2, 5, 3)),
annotations=[
Label(0,
attributes={
'positive_pairs': ['name0/name0_0001'],
'negative_pairs': ['name1/name1_0001']
})
]),
DatasetItem(
id='name1_0001',
subset='test',
image=np.ones((2, 5, 3)),
annotations=[
Label(1,
attributes={'positive_pairs': ['name1/name1_0002']})
]),
DatasetItem(id='name1_0002',
subset='test',
image=np.ones((2, 5, 3)),
annotations=[
Label(1,
attributes={
'positive_pairs': ['name1/name1_0002'],
'negative_pairs': ['name0/name0_0001']
})
]),
],
categories=['name0', 'name1'])
with TestDir() as test_dir:
LfwConverter.convert(source_dataset,
test_dir,
save_images=True,
save_dataset_meta=True)
parsed_dataset = Dataset.import_from(test_dir, 'lfw')
self.assertTrue(osp.isfile(osp.join(test_dir,
'dataset_meta.json')))
compare_datasets(self,
source_dataset,
parsed_dataset,
require_images=True)
def test_can_save_and_load_image_with_arbitrary_extension(self):
dataset = Dataset.from_iterable([
DatasetItem(id='a/1',
image=Image(path='a/1.JPEG', data=np.zeros((4, 3, 3))),
annotations=[Label(0)]),
DatasetItem(id='b/c/d/2',
image=Image(path='b/c/d/2.bmp',
data=np.zeros((3, 4, 3))),
annotations=[Label(1)]),
],
categories=['name0', 'name1'])
with TestDir() as test_dir:
LfwConverter.convert(dataset, test_dir, save_images=True)
parsed_dataset = Dataset.import_from(test_dir, 'lfw')
compare_datasets(self,
dataset,
parsed_dataset,
require_images=True)
def test_can_save_and_load_image_with_arbitrary_extension(self):
dataset = Dataset.from_iterable([
DatasetItem(id='name0/name0_0001', image=Image(
path='name0/name0_0001.JPEG', data=np.zeros((4, 3, 3))),
attributes={
'positive_pairs': [],
'negative_pairs': []
},
),
DatasetItem(id='name0/name0_0002', image=Image(
path='name0/name0_0002.bmp', data=np.zeros((3, 4, 3))),
attributes={
'positive_pairs': ['name0/name0_0001'],
'negative_pairs': []
},
),
])
with TestDir() as test_dir:
LfwConverter.convert(dataset, test_dir, save_images=True)
parsed_dataset = Dataset.import_from(test_dir, 'lfw')
compare_datasets(self, dataset, parsed_dataset, require_images=True)
def test_can_save_dataset_with_cyrillic_and_spaces_in_filename(self):
dataset = Dataset.from_iterable([
DatasetItem(id='кириллица с пробелом',
image=np.ones((2, 5, 3)),
attributes = {
'positive_pairs': [],
'negative_pairs': []
},
),
DatasetItem(id='name0/name0_0002',
image=np.ones((2, 5, 3)),
attributes = {
'positive_pairs': [],
'negative_pairs': ['кириллица с пробелом']
},
),
])
with TestDir() as test_dir:
LfwConverter.convert(dataset, test_dir, save_images=True)
parsed_dataset = Dataset.import_from(test_dir, 'lfw')
compare_datasets(self, dataset, parsed_dataset, require_images=True)
def test_can_save_and_load(self):
source_dataset = Dataset.from_iterable([
DatasetItem(id='name0/name0_0001',
subset='test', image=np.ones((2, 5, 3)),
attributes={
'positive_pairs': ['name0/name0_0002'],
'negative_pairs': []
}
),
DatasetItem(id='name0/name0_0002',
subset='test', image=np.ones((2, 5, 3)),
attributes={
'positive_pairs': ['name0/name0_0001'],
'negative_pairs': ['name1/name1_0001']
}
),
DatasetItem(id='name1/name1_0001',
subset='test', image=np.ones((2, 5, 3)),
attributes={
'positive_pairs': ['name1/name1_0002'],
'negative_pairs': []
}
),
DatasetItem(id='name1/name1_0002',
subset='test', image=np.ones((2, 5, 3)),
attributes={
'positive_pairs': ['name1/name1_0002'],
'negative_pairs': ['name0/name0_0001']
}
),
])
with TestDir() as test_dir:
LfwConverter.convert(source_dataset, test_dir, save_images=True)
parsed_dataset = Dataset.import_from(test_dir, 'lfw')
compare_datasets(self, source_dataset, parsed_dataset)